getml-mlflow
How to use
Prepare the Python environment.
$ uv venv
Install getml-mlflow via pip from pypi.
$ uv pip install getml-mlflow
Install latest getml-mlflow via pip from repository.
$ uv pip install "git+ssh://git@github.com/getml/getml-mlflow.git"
Run the mlflow server with its browser UI.
$ uv run mlflow ui
Open the mlflow UI in your browser.
$ open http://localhost:5000
Documentation
See User Guide
See API Reference
Log via mlflow
To log information from getML pipelines and its fit, score, predict and transform methods into mlflow, you can activate the mlflow autologging capabilities.
import getml_mlflow
getml_mlflow.autolog()
You can try this with our demonstrational notebooks and the community variants.
Delete a deleted experiment
By deleting an experiment in the mlflow UI, the experiment is still preset in the aether... Even when deleting the experiment via the mlflow CLI, the experiment is still present in the aether...
$ uv run mlflow experiments search --view all
Experiment Id Name Artifact Location
------------------ -------------- ------------------------------------
0 Default mlflow-artifacts:/0
888888888888888888 interstate94 mlflow-artifacts:/888888888888888888
$ uv run mlflow experiments delete -x 888888888888888888
Experiment with ID 888888888888888888 has been deleted.
Creating another experiment with the same name will result in the following error:
RestException: RESOURCE_ALREADY_EXISTS: Experiment 'interstate94' already exists in deleted state. You can restore the experiment, or permanently delete the experiment from the .trash folder (under tracking server's root folder) in order to use this experiment name again.
You have to delete the experiment from the aether via
$ rm -rf mlruns/.trash/888888888888888888/
$ MLFLOW_TRACKING_URI="http://localhost:5000" uv run mlflow gc
1 maintainer
Metadata
1 maintainer
Release files for getml-mlflow 0.1.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| getml_mlflow-0.1.2.tar.gz | 27.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| getml_mlflow-0.1.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 53.3 kB
Release files / getml_mlflow-0.1.2.tar.gz
| Download URL | getml_mlflow-0.1.2.tar.gz |
|---|---|
| Size | 27.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
uv/0.6.8
|
Release files / getml_mlflow-0.1.2-py3-none-any.whl
| Download URL | getml_mlflow-0.1.2-py3-none-any.whl |
|---|---|
| Size | 26.0 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
uv/0.6.8
|
